Systems Engineer - Machine Learning

The role

This person will build and optimize a platform that serves ML models to robots in real-time. They will integrate ML models into serving infrastructure and develop low-latency pipelines for robotics workloads.

What you will do

• Integrate and productionize state-of-the-art ML models into serving infrastructure
• Collaborate with research teams to bring new architectures from prototype to deployment
• Contribute to infrastructure tooling for faster and more reliable model onboarding
• Develop and maintain low-latency, high-throughput pipelines for ML model inference
• Optimize GPU workloads and accelerate ML frameworks for real-time performance

Required qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or relevant technical field, or equivalent practical experience
• 1+ years of experience in ML infrastructure, model serving, or backend systems engineering
• Strong Python
• Comfortable navigating unfamiliar research codebases and turning them into clean, production services
• Familiarity with ML frameworks (PyTorch, JAX)
• Familiarity with containerized deployments (Docker, Kubernetes)
• Familiarity with distributed serving frameworks (Ray, Triton, or similar)
• Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code tooling

Nice to have

• Familiarity with async Python, real-time communication protocols, and robotics systems

Benefits

• medical
• 401K
• other health benefits

Before you apply

• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
• Role is open to candidates currently based in and authorized to work in the US

About the company

General Robotics is an AI research and deployment company building a platform for general robot intelligence. Their mission is to enable rapid, robust, and safe deployment of general intelligence for autonomous systems and robotics.